---
title: "COVID-19 in LAC"
output:
flexdashboard::flex_dashboard:
logo: rbmv_curve.png
orientation: rows
source_code: embed
theme: flatly
---
```{r setup, include=FALSE}
library(flexdashboard)
```
```{r, include=FALSE}
library(tidyverse)
library(lubridate)
library(rvest)
library(sf)
library(leaflet)
library(plotly)
library(rbmv)
`%<>%` <- magrittr::`%<>%`
dph_covid19_page <- read_html("http://www.publichealth.lacounty.gov/media/Coronavirus/locations.htm")
dph_covid19_tbls <- dph_covid19_page %>%
html_nodes("table") %>%
html_table()
dph_covid19_messy <- dph_covid19_tbls[[1]] %>%
repair_names() %>%
janitor::clean_names() %>%
rename(locations = x1, total_cases = x2) %>%
select(-x3)
dph_covid19_totals <- dph_covid19_messy %>%
slice(2:11)
dph_covid19_age_groups <- dph_covid19_messy %>%
slice(14:18) %>%
rename(age_group = locations) %>%
mutate(total_cases = parse_number(total_cases))
dph_covid19_gender <- dph_covid19_messy %>% slice(20:24) %>%
rename(gender = locations) %>%
mutate(total_cases = parse_number(total_cases))
lac_total_cases <- parse_number(dph_covid19_totals$total_cases[[1]])
lac_total_deaths <- parse_number(dph_covid19_totals$total_cases[[6]])
dph_covid19_totals %>%
mutate(locations = str_remove_all(locations, "- ")) %>%
filter(locations %in% c("Long Beach", "Pasadena")) %>%
slice(1:2) %>%
mutate(locations = str_glue("City of {locations}") %>% parse_character(),
total_cases = parse_number(total_cases)) -> lb_pass
dph_covid19 <- dph_covid19_messy %>% slice(30:365) %>%
mutate(
locations = str_remove_all(locations, regex("\\*")),
total_cases = parse_number(total_cases, na = "--"),
locations = case_when(
str_detect(locations, "San Francisquito") ~ "Unincorporated - San Francisquito Canyon/Bouquet Canyon",
TRUE ~ locations)) %>%
filter(!locations == "Los Angeles") %>%
bind_rows(., lb_pass)
captions <- dph_covid19_page %>%
html_nodes("caption") %>%
html_text()
str_remove_all(captions[1], "\\r|\\n|\\t") %>%
str_split_fixed(., "\\*", 2) -> page_updated
page_updated <- str_split_fixed(page_updated[1], " ", 4)[4]
page_updated <- str_glue("{page_updated}/20")
page_updated <- parse_date(page_updated, "%m/%d/%y")
# uncomment line below if the 'caption' html is not updated on DPH website
page_updated <- Sys.Date()
page_updated_string <- str_glue("{wday(page_updated, label = T)} {month(page_updated, label = T)} {day(page_updated)}, {year(page_updated)}")
gis <- st_read(
dsn = "data/gis/geo_export_871186bb-3266-4a1c-a0f6-8cda86b55d55.shp",
layer = "geo_export_871186bb-3266-4a1c-a0f6-8cda86b55d55",
quiet = T
)
gis %<>% st_transform(crs = 4326)
health_profile <- read_csv("data/Los_Angeles_County_City_and_Community_Health_Profiles_2018.csv")
lac_covid19 <- gis %>%
left_join(., dph_covid19, by = c("label" = "locations")) %>%
left_join(., health_profile, by = c("lcity" = "GEONAME")) %>%
mutate(total_cases = if_else(is.na(total_cases), 0, total_cases))
covid19_cases <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv")
covid19_deaths <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_US.csv")
covid19_time_series_cases <- covid19_cases %>%
filter(Admin2 == "Los Angeles") %>%
gather("date", "cases", 12:ncol(covid19_cases)) %>%
select(Admin2, date, cases) %>%
rename(county = Admin2) %>%
mutate(date = parse_date(date, "%m/%d/%y"),
case_type = "New Confirmed Case") %>%
bind_rows(
tribble(
~county, ~date, ~cases, ~case_type,
"Los Angeles", page_updated, lac_total_cases, "New Confirmed Case")) %>%
distinct()
covid19_time_series_deaths <- covid19_deaths %>%
filter(Admin2 == "Los Angeles") %>%
gather("date", "cases", 13:ncol(covid19_deaths)) %>%
select(Admin2, date, cases) %>%
rename(county = Admin2) %>%
mutate(date = parse_date(date, "%m/%d/%y"),
case_type = "Death") %>%
bind_rows(
tribble(
~county, ~date, ~cases, ~case_type,
"Los Angeles", page_updated, lac_total_deaths, "Death")) %>%
distinct()
covid19_time_series <- bind_rows(covid19_time_series_cases, covid19_time_series_deaths)
outbreaks <- c(
"New York City, New York, US", "Nassau, New York, US", "Suffolk, New York, US",
"Westchester, New York, US", "Cook, Illinois, US", "Wayne, Michigan, US",
"Bergen, New Jersey, US", "Hudson, New Jersey, US",
"Essex, New Jersey, US")
covid19_cases_top10_us <- covid19_cases %>%
filter(Combined_Key %in% outbreaks) %>%
gather("date", "cases", 12:ncol(covid19_cases)) %>%
select(Combined_Key, date, cases) %>%
rename(location = Combined_Key) %>%
mutate(date = parse_date(date, "%m/%d/%y"),
case_type = "New Confirmed Case") %>%
distinct() %>%
arrange(date, desc(cases))
light_blue <- rbmv_pal("main", plotly = T)[1]
ruby <- rbmv_pal("main", plotly = T)[2]
pale_black <- rbmv_pal("main", plotly = T)[5]
```
LA County {data-icon="fa-map"}
=====================================
Row {data-height=505}
-------------------------------------
###
```{r}
bins <- c(0, 25, 50, 75, 100, 140, 180, 200, 240, 280, 300, 340, Inf)
pal <- colorBin(
palette = rbmv_pal("spectrum", plotly = T),
domain = lac_covid19$total_cases,
bins = bins)
mapbox <- "https://api.mapbox.com/styles/v1/robertmitchellv/cipr7teic001aekm72dnempan/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1Ijoicm9iZXJ0bWl0Y2hlbGx2IiwiYSI6ImNpcHI2cXFnbTA3MHRmbG5jNWJzMzJtaDQifQ.vtvgLokcc_EJgnWVPL4vXw"
label <- str_glue("{lac_covid19$label}
Total cases: {lac_covid19$total_cases}") %>%
lapply(htmltools::HTML)
lac_covid19 %>%
leaflet() %>%
addTiles(mapbox, attribution = paste("Data from Los Angeles County Department of Publich Health COVID-19 location table")) %>%
addPolygons(
fillColor = ~pal(total_cases),
weight = 1.5,
fillOpacity = 0.7,
smoothFactor = 0.5,
color = "white",
label = label,
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto")) %>%
addLegend(
pal = pal, values = ~total_cases, opacity = 0.7,
title = NULL, position = "bottomright") %>%
setView(-118.2, 34, zoom = 9.5)
```
Row {data-height=320}
-------------------------------------
###
```{r}
source <- list(
x = 1, y = -0.24, text = "Source: 2019 Novel Coronavirus COVID-19 (2019-nCoV)\nData Repository by Johns Hopkins CSSE",
showarrow = F, xref = "paper", yref = "paper", xanchor = "right", yanchor = "auto",
xshif = 0, yshift = 0, font = list(size = 9, color = "grey")
)
covid19_cases_top10_us %>%
plot_ly(x = ~date, y = ~cases, color = ~location, line = list(color = rbmv_pal(plotly = T)[3], width = .75),
type = "scatter", mode = "lines", hoverinfo = "text",
text = ~paste(" Location: ", location,
" Case type: ", case_type,
" Cases: ", cases)) %>%
add_trace(x = ~date, y = ~cases, color = ~county, line = list(color = rbmv_pal(plotly = T)[2], width = 2),
data = covid19_time_series_cases, hoverinfo = "text",
text = ~paste(" Location: ", county,
" Case type: ", case_type,
" Cases: ", cases)) %>%
layout(title = " ",
xaxis = list(title = " "),
yaxis = list(title = "Log(Cases)\n", type = "log"),
margin = list(b = 50),
legend = list(
title = list(text = " How LA County's COVID-19 Cases Compare Across the US "),
x = 100, y = .99, font = list(size = 9)),
annotations = source) %>%
config(displayModeBar = FALSE)
```
Row {data-height=175}
-------------------------------------
###
```{r}
valueBox(page_updated_string, color = light_blue, icon = "fa-calendar", caption = "Data pulled from both LAC DPH and John Hopkins CSSE")
```
###
```{r}
total_cases <- scales::comma(last(covid19_time_series_cases$cases))
valueBox(total_cases, color = ruby, icon = "fa-ambulance", caption = "Total Lab Confirmed COVID-19 Cases in LAC")
```
###
```{r}
total_deaths <- scales::comma(last(covid19_time_series_deaths$cases))
valueBox(total_deaths, color = pale_black, icon = "fa-medkit", caption = "Total COVID-19 Related Deaths")
```
